Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 9 of 9 for “"Ensemble Approaches"”.
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WDR5 Network Analysis Using Ensemble Approaches
… protein-5 (RbBP5). In this work we used multiple ensemble measurement based bulk-phase techniques to characterize WDR5's interactions. We utilized biolayer interferometry (BLI) and surface plasmon resonance (SPR) to calculate the association and dissociation rate constants. Furthermore, we used …
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Multi-sensor rainfall data assimilation using ensemble approaches
… The characterization takes the form of an ensemble of rainfall replicates, each conditioned on multiple measurement sources. The conditional replicates are obtained from ensemble data assimilation algorithms (Kalman filters and smoothers) based on a recursive cluster rainfall model. …
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Multi-sensor large scale land surface data assimilation using ensemble approaches
One of the ensemble Kalman filter's (EnKF) attractive features in land surface applications is its ability to provide distributional information. The EnKF relies on normality approximations that improve its efficiency but can also compromise the accuracy of its distributional estimates. The effects …
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DWCox: A density-weighted Cox model for outlier-robust prediction of prostate cancer survival
… applications. More complex methods, like ensemble approaches, have the potential of reaching better prediction accuracy at the cost of increased training difficulty and worse result interpretability. Better performance on a specific data set may also be obtained by extensive manual …
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De Novo Transcription Factor Binding Site Discovery: A Machine Learning And Model Selection Approach
… and to manually compare the results. Recently, ensemble approaches have been proposed that automate the execution of a set of tools and aggregate the results. This has been seen to provide some improvement but is still handled in an ad hoc manner since tool outputs are often in dissimilar …
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Uncertainty Estimation in Deep Learning with application to Spoken Language Assessment
… part of this thesis uncertainty estimation via ensemble and single-model approaches is discussed in detail and a new class of models for uncertainty estimation, called $\textit{Prior Networks}$, is proposed. Prior Networks are able to $\textit{emulate}$ an ensemble of models using a single …
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Multi-output structured learning
… is akin to the spirit of mixture models or ensemble approaches. However, in this work we dispense with component weights and delay commitment to single predictions. In doing so, we advocate for pipelined approaches where multiple hypotheses are fed forward for refinement, aggregation, …
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An application of climate change ensemble averaging methods to fisheries management
… (also termed Operating Models, or OMs) in an ensemble is used. In order to address these problems, a number of methods used in climate change to address similar problems are applied in the case of the hake fishery. The aim is to determine the impact that the application of the model ensemble …